Figma Context MCP
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
제작자가 쓴 설명(영어 원문)
Compose and render video from one JSON template. Deterministic, runs locally, no generative model.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
LECLAP_MCP_OUTPUT_DIR, LECLAP_MCP_MEDIA_DIR, LECLAP_MCP_RENDER_TIMEOUT_MS, LECLAP_MCP_ALLOW_REMOTION, LECLAP_MCP_REMOTION_ENTRY필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"video": {
"command": "npx",
"args": [
"-y",
"@leclap/mcp"
],
"env": {
"LECLAP_MCP_OUTPUT_DIR": "your-value",
"LECLAP_MCP_MEDIA_DIR": "your-value",
"LECLAP_MCP_RENDER_TIMEOUT_MS": "your-value",
"LECLAP_MCP_ALLOW_REMOTION": "your-value",
"LECLAP_MCP_REMOTION_ENTRY": "your-value"
}
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add video --env LECLAP_MCP_OUTPUT_DIR=your-value --env LECLAP_MCP_MEDIA_DIR=your-value --env LECLAP_MCP_RENDER_TIMEOUT_MS=your-value --env LECLAP_MCP_ALLOW_REMOTION=your-value --env LECLAP_MCP_REMOTION_ENTRY=your-value -- npx -y @leclap/mcp실행하기 전에 빈 값을 채워 주세요.
프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"video": {
"command": "npx",
"args": [
"-y",
"@leclap/mcp"
],
"env": {
"LECLAP_MCP_OUTPUT_DIR": "your-value",
"LECLAP_MCP_MEDIA_DIR": "your-value",
"LECLAP_MCP_RENDER_TIMEOUT_MS": "your-value",
"LECLAP_MCP_ALLOW_REMOTION": "your-value",
"LECLAP_MCP_REMOTION_ENTRY": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"video": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@leclap/mcp"
],
"env": {
"LECLAP_MCP_OUTPUT_DIR": "your-value",
"LECLAP_MCP_MEDIA_DIR": "your-value",
"LECLAP_MCP_RENDER_TIMEOUT_MS": "your-value",
"LECLAP_MCP_ALLOW_REMOTION": "your-value",
"LECLAP_MCP_REMOTION_ENTRY": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
LECLAP_MCP_OUTPUT_DIR envLECLAP_MCP_MEDIA_DIR envLECLAP_MCP_RENDER_TIMEOUT_MS envLECLAP_MCP_ALLOW_REMOTION envLECLAP_MCP_REMOTION_ENTRY env이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 6일 점검
레지스트리 이름이 도메인 leclap.dev 기준으로 확인되었어요(레지스트리가 도메인 소유를 확인해요)
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.3.4)은 2개월 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Node.js도 있어야 해요.
같은 카테고리에는: Figma Context MCP, Claude Real Video, Figma MCP Server
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
Let any LLM watch a video locally — and search everything it has ever watched.
The Figma MCP server brings Figma design context directly into your AI workflow.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
Connect your AI agent to LeClap’s video engine. Discover samples, author a template, validate it, inspect real frames, revise and render. Start with the agent guide.
An MCP server that exposes the ffmpeg-video-composer engine as agent-callable video tools.
An AI agent (Claude Desktop, Cursor, …) is the LLM; this server helps it author a customized template with nice effects from the schema, then validates and renders it deterministically to an mp4. The server includes the 50 showcase samples through the shared packaged catalog, with creative direction, descriptors and required inputs. It works without the app or private creative-kit at runtime. Remotion-assisted authoring is an optional path. The result is _agent-composable, deterministic, reproducible_ video — the opposite of generative video models, which sample rather than render.
| Tool | Description |
|---|---|
get_samples | Without id: sample metadata and required inputs, filtered by category/backend/query → { samples }; with id: that sample with its self-contained template JSON |
get_template_schema | The JSON Schema for a template descriptor + a short authoring guide |
get_motion_catalog | Motion presets, camera, graphics, transitions, easing/time grammar, themes, platforms, genre doctrine and scene blueprints; { query, kind? } → ranked matches (a query matching nothing is logged to the catalog gap log) |
validate_template | Dry-run an inline descriptor (no render) → { valid, sectionCount, orientation, requiredClips, formFields, fields?, geometry?, featureWarnings? }; include: ["resolved"] adds resolved (the descriptor for fields/format), include: ["timeline"] adds timeline (sections, motion events, beats, cues) |
compose_video | Validate an inline descriptor and render (one format of it, optionally) → { outputPath, durationSeconds, sizeBytes, videoCodec, audioCodec, renderId }, plus a resource_link to the mp4 |
render_frames | Render a native template and return still frames as PNG images + paths: at, atTransitions, perSection, sheet, safe, zoom, variants, looks |
edit_template | JSON Patch operations and/or registered effectProps by section name over inline JSON, under expectedRevision, all-or-nothing → { template, revision, changedPaths, changedSections? } |
probe_media | Inspect a local media file → codecs, duration, sample rate, size, and HDR / colour / bit depth / VFR / rotation traits |
extract_style | Reference image/clip under the media dir → { theme, styleGuide, confidence }: palette roles + WCAG contrast, grain, pacing (palette and pacing only) |
extract_structure | A reference clip's format (shots, rhythm, transitions, grounds, layout) as binding rules for a template. Format only; samples every 0.25 s for up to 2 minutes. |
extract_brand | A website's brand kit (name, colours, fonts, logo) as a theme and binding rules, saved under /brand-kits/ /. Needs --allow-network. |
analyze_music | Measure a local music file → { bpm, offset, beatsPerBar, confidence, usable, cues, globalBeats } for global.beats and cue:drop |
analyze_sound | Render an sfx[].sound (composed, or a preset with variations) → length, peak/RMS dBFS, centroid, high/low energy shares, attack, advisories + spectrogram and waveform PNGs |
transcribe_media | Transcribe a local audio/video file's speech with whisper.cpp, locally → { words, srt, language, confidence, advice } to pin into subtitles.words |
get_capabilities | Local FFmpeg capability report (listings + one-frame probes) → each feature yes/no/unknown with a fix |
open_in_builder | Template → a leclap.dev/studio/builder#t=… link for a person to edit it; the template rides in the URL fragment (never sent to a server) → { url, length, mediaToRebind, warnings } |
render_remotion_clip | _(bonus, opt-in)_ Render a composition from your own Remotion project → an mp4 clip for a project_video section |
analyze_sound seeds a sound's noise and jitter with seed (default 0). To hear the exact render a template will play, pass the template's global.seed as seed and the cue's path as cue: "sections.intro.sfx[0]" for the first cue of the section named intro, "global.sfx[2]" for the third global cue. The tool then seeds the sound as the mix seeds that cue and returns the seed it used. Levels are floored at -120 dBFS, so a silent sound reads -120 and raises sound_silent.
Typical agent flow: get_samples → get_samples { id } → inspect requirements and customize media/copy → get_template_schema → validate_template (iterate until valid) → render_frames (look at the result; check safe zones with safe) → compose_video → read the returned outputPath. Author a fresh descriptor from the schema when no sample fits.
render_frames renders through a per-section cache under /.section-cache, so a second look after a small edit re-encodes only the sections that changed. It runs in the render worker under the same media-dir checks, slot cap, timeout and cancellation as compose_video, writes PNGs to /frames- /, and inlines at most eight images (the sheets when sheet is set). Moments are seconds or time references on the whole video: "intro.end" (a section or an element id), "50%", "beat:8", "cue:drop + 0.1". validate_template with include: ["timeline"] lists the moments worth picking.
validate_template also reports, render-free, text that would run off the frame or out of title-safe, collide with other text, sit under a band, be too small, lack contrast, or sit over footage with no box, outline or shadow. Those findings arrive on the optional geometry field — one line each, saying what to change, and the field is absent entirely when there is nothing to fix. They are advisory: valid stays true. A line ending (approx: …) says why it is an estimate: the font could not be read, the text carries a {{ variable }} that only resolves at render time, or a section declares no duration. When a font is not bundled, the server fetches it from the LeClap asset catalog (5s timeout); offline, it estimates.
Pass render: true to validate_template to also render the sections that hold text and measure their contrast from real pixels — it settles text over images, grades and looks that the render-free check can only call unknown. It costs seconds (two renders of those sections), goes through the same media-dir sandbox as compose_video, reads assets from the media dir, and runs in the same forked render worker under the same timeout. It adds a render field (measured, seconds, and unavailable when it could not render — no FFmpeg with drawtext, a failed render, or a timeout); the render-free findings come back either way.
get_samples is always available, even with Remotion disabled. It reads packaged data only: no media downloads, effect execution or repository access. Without id it lists, filtered by optional category (templates, typography, effects, app-demos, overlays, evidence), backend (native, remotion) and case-insensitive query (up to 4000 characters). With id (1–200 characters) it returns that sample.
{ "name": "get_samples", "arguments": { "category": "app-demos", "backend": "native" } }
{ "name": "get_samples", "arguments": { "id": "web-app-promo" } }
Results include identical JSON in text and structuredContent; with id, the descriptor sits at template alongside its metadata. Unknown IDs return isError with a discovery hint. Required inputs include named clips and durations/capture hints, form fields and limits, variables/defaults/placeholders, assets, effective preset font files (source: "preset") and versioned effects. Replace the sample copy, supply clips by userVideoPaths and form values by fields, customize global.variables, then pass template to validate_template and compose_video. Referenced partials are embedded in the descriptor.
The 25 native samples use FFmpeg; the 10 registered effect samples require --allow-remotion, Remotion peers and a trusted --remotion-entry. Effects with customCatalog: true also require the operator's --effect-catalog and the matching composition in that entry. Sample discovery does not enable execution, install a catalog or supply React source. Inspect requirements.setup and, after operator setup, get_effect_schema before editing effect props. See operator catalogs.
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